Near-Surface Motion in the Nocturnal, Stable Boundary Layer Observed with Fibre-Optic Distributed Temperature Sensing
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The evolution of cold air layers near the surface was investigated for a night with stable conditions near the surface. Spatial air temperature observations at 276 co-located vertical profiles were made using high-resolution fibre-optic based distributed temperature sensing (DTS) in a quasi three-dimensional geometry oriented along a shallow depression in the landscape and analysed for patterns in near-surface flow. Temperature stratification was observed to be interrupted by transient temperature structures on the scale of metres for which the flow direction and velocity could be quantified. The high spatial resolution and large spatial domain of the DTS revealed temperature structures in a level of detail that exceeded the capability of traditional point observations of air temperature at low wind speeds. Further, composition techniques were applied to describe wave-like motions in the opposite direction of the mean flow, at intervals of approximately 200 s (5 mHz). The DTS technique delivered tomography on a scale of tens of metres. The spatial observations at high spatial (fractions of a metre) and temporal (sec) resolution provided new opportunities for detection and quantification of surface-flow features and description of complicated scale interactions. High-resolution DTS is therefore a valuable addition to experimental research on stable and weak-wind boundary layers near the surface.
KeywordsCold-air pool Distributed temperature sensing Stable boundary layer Sub-mesoscale Surface flow Tomography Turbulence
This research was funded by the Army Research Office, contracts W911NF-10-1-0361 and W911NF-09-1-0271, and the National Science Foundation, awards AGS 0955444. MJZ received additional support through the Helmholtz Association REKLIM initiative. The fibre-optics instrumentation was provided by the Center for Transformative Environmental Monitoring Programs (CTEMPS) funded by the National Science Foundation, award EAR 0930061. We thank Javier Orozco, Stephen Drake, Alex Smooth and Steve Cluskey (at OSU) for assistance in the field, as well as Chadi Sayde and Javier Benitez (at OSU) for support with fibre-optics. The topographic map was derived using data provided by the Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar Program and services provided by the OpenTopography Facility with support from the National Science Foundation, awards 0930731 and 0930643.
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